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Strategies for Improving the Tolerance of Canola Plants to Abiotic Stress
Project
Project code: JKI-SF-08-1257
Contract period: 01.11.2018
- 31.10.2020
Purpose of research: Applied research
Among the overall massive food self-sufficiency gap in Egypt, the insufficiency in edible oil supply is especially severe with around 97% of edible oils being imported nowadays. Canola (Brassica napus L.), Germany’s by far most important oil crop covering more than 10% of Germany’s total arable land has been identified as a promising crop to be cultivated in Egypt to help close the huge oil supply gap. Canola interrupts the cereal dominated crop rotations, and has certain potential to be cultivated under moderately saline soil conditions, which constitutes a major production constraining factor in Egyptian agriculture. Thus the goal of the current project is to increase the productivity of canola cultivation in Egypt by improving its tolerance to abiotic stress. An integrated research approach is applied, that screens the existing range of German and Egyptian canola cultivars with regard to their tolerance to salinity and heat stress. In experiments under controlled environments and natural field conditions selected cultivars will be evaluated according to their phenological, morphological and physiological characteristics and reactions towards abiotic stress. To identify promising cultivars for specific production conditions and regions of Egypt, marker assisted analysis is applied in combination with a crop simulation model approach. In that way the limited project duration can be used efficiently by analyzing the Genotype*Environment*Management interaction over various Egyptian production sites, and important information can be provided to plant breeders regarding desired traits and suitable ideotypes of canola. The project will help to strongly enhance the efficiency and profitability of canola production in Egypt and other semi-arid and arid regions of the world.
Section overview
Subjects
- Plant Breeding
- Specialised crops
